Litcius/Paper detail

An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection

Jose Pérez-Cano, Yunan Wu, Arne Schmidt, Miguel López-Pérez, Pablo Morales-Álvarez, Rafael Molina, Aggelos K. Katsaggelos

2023Expert Systems with Applications10 citationsDOI

Topics & Concepts

Computer scienceArtificial intelligenceRobustness (evolution)Machine learningClassifier (UML)Feature extractionEnd-to-end principleGaussian processPattern recognition (psychology)Data miningGaussianBiochemistryQuantum mechanicsChemistryGenePhysicsMachine Learning in HealthcareIntracerebral and Subarachnoid Hemorrhage ResearchAI in cancer detection
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection | Litcius